Pharmacodynamic modelling of biomarker data in oncology

Prospective approaches to gene therapy computational modeling - spotlight on viral gene therapy

Clinical studies have found there still exists a lack of gene therapy dose-toxicity and dose-efficacy data that causes gene therapy dose selection to remain elusive. Model informed drug development (MIDD) has become a standard tool implemented throughout the discovery, development, and approval of pharmaceutical therapies, and has the potential to inform dose-toxicity and dose-efficacy relationships to support gene therapy dose selection. Despite this potential, MIDD approaches for gene therapy remain immature and require standardization to be useful for gene therapy clinical programs. With the goal to advance MIDD approaches for gene therapy, in this review we first provide an overview of gene therapy types and how they differ from a bioanalytical, formulation, route of administration, and regulatory standpoint. With this biological and regulatory background, we propose how MIDD can be advanced for AAV-based gene therapies by utilizing physiological based pharmacokinetic modeling and quantitative systems pharmacology to holistically inform AAV and target protein dynamics following dosing. We discuss how this proposed model, allowing for in-depth exploration of AAV pharmacology, could be the key the field needs to treat these unmet disease populations.

Optimization of blood pressure measurement practices for pharmacodynamic analyses of tyrosine-kinase inhibitors

Blood pressure measurements form a critical component of adverse event monitoring for tyrosine kinase inhibitors, but might also serve as a biomarker for dose titrations. This study explored the impact of various sources of within-individual variation on blood pressure readings to improve measurement practices and evaluated the utility for individual- and population-level dose selection. A pharmacokinetic-pharmacodynamic modeling framework was created to describe circadian blood pressure changes, inter- and intra-day variability, changes from dipper to non-dipper profiles, and the relationship between drug exposure and blood pressure changes over time. The framework was used to quantitatively evaluate the influence of physiological and pharmacological aspects on blood pressure measurements, as well as to compare measurement techniques, including office-based, home-based, and ambulatory 24-h blood pressure readings. Circadian changes, as well as random intra-day and inter-day variability, were found to be the largest sources of within-individual variation in blood pressure. Office-based and ambulatory 24-h measurements gave rise to potential bias (>5 mmHg), which was mitigated by model-based estimations. Our findings suggest that 5-8 consecutive, home-based, measurements taken at a consistent time around noon, or alternatively within a limited time frame (e.g., 8.00 a.m. to 12.00 p.m. or 12.00 p.m. to 5.00 p.m.), will give rise to the most consistent blood pressure estimates. Blood pressure measurements likely do not represent a sufficiently accurate method for individual-level dose selection, but may be valuable for population-level dose identification. A user-friendly tool has been made available to allow for interactive blood pressure simulations and estimations for the investigated scenarios.

Current Approaches of Building Mechanistic Pharmacodynamic Drug-Target Binding Models

Mechanistic pharmacodynamic models that incorporate the binding kinetics of drug-target interactions have several advantages in understanding target engagement and the efficacy of a drug dose. However, guidelines on how to build and interpret mechanistic pharmacodynamic drug-target binding models considering both biological and computational factors are still missing in the literature. In this chapter, current approaches of building mechanistic PD models and their advantages are discussed. We also present a methodology on how to select a suitable model considering both biological and computational perspectives, as well as summarize the challenges of current mechanistic PD models.

Integrating Molecular Biomarker Inputs Into Development and Use of Clinical Cancer Therapeutics

Biomarkers can contribute to clinical cancer therapeutics at multiple points along the patient’s diagnostic and treatment course. Diagnostic biomarkers can screen or classify patients, while prognostic biomarkers predict their survival. Biomarkers can also predict treatment efficacy or toxicity and are increasingly important in development of novel cancer therapeutics. Strategies for biomarker identification have involved large-scale genomic and proteomic analyses. Pathway-specific biomarkers are already in use to assess the potential efficacy of immunotherapy and targeted cancer therapies. Judicious application of machine learning techniques can identify disease-relevant features from large data sets and improve predictive models. The future of biomarkers likely involves increasing utilization of liquid biopsy and multiple samplings to better understand tumor heterogeneity and identify drug resistance.

Metformin induces a fasting- and antifolate-mimicking modification of systemic host metabolism in breast cancer patients

Certain dietary interventions might improve the therapeutic index of cancer treatments. An alternative to the “drug plus diet” approach is the pharmacological reproduction of the metabolic traits of such diets. Here we explored the impact of adding metformin to an established therapeutic regimen on the systemic host metabolism of cancer patients. A panel of 11 serum metabolites including markers of mitochondrial function and intermediates/products of folate-dependent one-carbon metabolism were measured in paired baseline and post-treatment sera obtained from HER2-positive breast cancer patients randomized to receive either metformin combined with neoadjuvant chemotherapy and trastuzumab or an equivalent regimen without metformin. Metabolite profiles revealed a significant increase of the ketone body β-hydroxybutyrate and of the TCA intermediate α-ketoglutarate in the metformin-containing arm. A significant relationship was found between the follow-up levels of homocysteine and the ability of treatment arms to achieve a pathological complete response (pCR). In the metformin-containing arm, patients with significant elevations of homocysteine tended to have a higher probability of pCR. The addition of metformin to an established anti-cancer therapeutic regimen causes a fasting-mimicking modification of systemic host metabolism. Circulating homocysteine could be explored as a clinical pharmacodynamic biomarker linking the antifolate-like activity of metformin and biological tumor response.

Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy

The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed "cyclotherapy". Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs.

Dose-biomarker-response modeling of the anticancer effect of ethaselen in a human non-small cell lung cancer xenograft mouse model

Thioredoxin reductase (TrxR) is a component of several redox-sensitive signaling cascades that mediate important biological processes such as cell survival, maturation, growth, migration and inhibition of apoptosis. The expression levels of TrxR1 in some human carcinoma cell lines are nearly 10 times higher than those in normal cells. Ethaselen is a novel antitumor candidate that exerts potent inhibition on non-small cell lung cancer (NSCLC) by targeting TrxR. In this study we explored the relationship between the ethaselen dose and TrxR activity level and the relationship between TrxR degradation and tumor apoptosis in a human lung carcinoma A549 xenograft model. BALB/c nude mice implanted with human NSCLC cell line A54 were administered ethaselen (36, 72, 108 mg·kg^-1·d^-1, ig) or vehicle for 10 d. The tumor size and TrxR activity levels in tumor tissues were daily recorded and detected. Based on the experimental data, NONMEM 7.2 was used to develop an integrated dose-biomarker-response model for describing the quantitative relationship between ethaselen dose and tumor eradication effects. The time course of TrxR activity levels was modeled using an indirect response model (IDR model), in which the influence of the tumor growth rates on K_in with the linear correction factor γ1 (0.021 d/mm). The drug binding-inhibition effects on K_out was described using a sigmoidal E_max model with S_max (5.95), SC₅₀ (136 mg/kg) and Hill's coefficient γ2 (2.29). The influence of TrxR activity inhibition on tumor eradication was characterized by an E_max model with an E_max (130 mm³/d) and EC₅₀ (0.0676). This model was further validated using a visual predictive check (VPC) and was used to predict the efficacy of different doses. In conclusion, the properties and characteristics of ethaselen acting on TrxR degradation and subsequently resulting in tumor apoptosis are characterized by the IDR model and integrated dose-biomarker-response model with high goodness-of-fit and great predicative ability. This approach shed new light on the detailed processes and mechanism of ethaselen action and may offer a valuable reference for an appropriate dosing regimen for use in further clinical applications.

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

AIM

The novel anticancer compound TM208 is an EGFR tyrosine kinase inhibitor (EGFR-TKI). Since the development of resistance to EGFR-TKIs is a major challenge in their clinical usage, we investigated the profiles of resistance following continuous treatment with TM208 in human breast cancer xenograft mice, and identified the relationship between the tumor pEGFR levels and tumor growth inhibition.

METHODS

Female BALB/c nude mice were implanted with human breast cancer MCF-7 cells, and the xenograft mice received TM208 (50 or 150 mg·kg(-1)·d(-1), ig) or vehicle for 18 d. The pharmacokinetics (PK) and pharmacodynamics (PD) of TM208 were evaluated.

RESULTS

The PK properties of TM208 were described by a one-compartment model with first-order absorption kinetics. Our study showed the inhibitory effects of TM208 on tumor pEGFR levels gradually reached a maximum effect, after which it became weaker over time, which was characterized by a combined tolerance/indirect response PD model with an estimated EC50 (55.9 μg/L), as well as three parameters ('a' of 27.2%, 'b' of 2730%, 'c' of 0.58 h(-1)) denoting the maximum, extent and rate of resistance, respectively. The relationship between the tumor pEGFR levels and tumor growth inhibition was characterized by a combined logistic tumor growth/transit compartment model with estimated parameters associated with tumor growth characteristics kng (0.282 day(-1)), drug potency kTM208 (0.0499 cm(3)/day) and the kinetics of tumor cell death k1 (0.141 day(-1)), which provided insight into drug mechanisms and behaviors.

CONCLUSION

The proposed PK/PD model provides a better understanding of the pharmacological properties of TM208 in the treatment of breast cancer. Furthermore, simulation based on a tolerance model allows prediction of the occurrence of resistance.

Validation of a flow cytometry-based assay to assess C5aR receptor occupancy on neutrophils and monocytes for use in drug development

The C5a/C5a receptor (C5aR) pathway, a key component in the proinflammatory immune response, is an attractive therapeutic target since its dysregulation is implicated in a variety of autoimmune and inflammatory disorders. The objective of the present study was to validate a receptor occupancy (RO) assay for a human anti-C5aR monoclonal antibody drug candidate, NNC0215-0384 (NN0384). This flow cytometry-based assay measures the percentage (%), median fluorescence intensity (MFI), and molecules of equivalent soluble fluorochrome (MESF) of NN0384 binding to its target cells, neutrophils and monocytes, in whole blood from normal healthy donors and rheumatoid arthritis (RA) patients with clinically active disease. The validation parameters assessed included postcollection and postprocessing sample stability, intra- and interassay precision, an analyst-to-analyst comparison, a comparison of normal healthy donor and RA patient sample postcollection stability, and a laboratory-to-laboratory comparison and assay transfer. The cumulative results indicate that the assay was reproducible, met the clearly defined acceptance criteria for the validation parameters tested, and was transferable to another laboratory. In conclusion, this RO assay is suitable for use to accrue pharmacodynamic biomarker data in a multicenter, global clinical trial.

Molecularly targeted cancer therapy: some lessons from the past decade

The tremendous advances achieved in the understanding of cancer biology have delivered unprecedented progress in molecularly targeted cancer therapy in the past decade. The fast growing category of targeted anticancer agents available for clinical use is accompanied by a conceptual revolution in anticancer drug development. Nevertheless, molecularly targeted cancer therapy remains challenged by a high failure rate and an extremely small proportion of patients that can benefit. It is pivotal to take lessons from the past and seek new solutions. This review discusses conceptual progress and remaining challenges in molecularly targeted cancer therapy, and proposes feasible alternatives to increase chances of clinical success in the future.

Pharmacokinetic-pharmacodynamic modeling of the anticancer effect of erlotinib in a human non-small cell lung cancer xenograft mouse model

AIM

Erlotinib is used to treat non-small-cell lung cancer (NSCLC), which targets epidermal growth factor receptor (EGFR) tyrosine kinase. The aim of this study was to investigate the relationship between erlotinib plasma concentrations and phosphorylated EGFR (pEGFR) levels, as well as the relationship between pEGFR levels and tumor growth inhibition in a human non-small-cell lung cancer xenograft mouse model.

METHODS

Female BALB/c nude mice were implanted with the human NSCLC cell line SPC-A-1. The animals were given via gavage a single dose of erlotinib (4, 12.5, or 50 mg/kg). Pharmacokinetics of erlotinib was determined using LC-MS/MS. Tumor volume and pEGFR levels in tumor tissues were measured at different time points after erlotinib administration. The levels of pEGFR in tumor tissues was detected using Western blotting and ELISA assays.

RESULTS

The pharmacokinetics of erlotinib was described by a two-compartment model with first order extravascular absorption kinetics. There was a time delay of approximately 2 h between erlotinib plasma concentrations and pEGFR degradation. The time course of pEGFR degradation was reasonably fit by the indirect response model with a calculated IC50 value of 1.80 μg/mL. The relationship between pEGFR levels and tumor volume was characterized by the integrated model with a Kbio value of 0.507 cm(3)/week, which described the impact of pEGFR degradation on tumor growth.

CONCLUSION

The pharmacokinetic/pharmacodynamic properties of erlotinib in a human tumor xenograft model were described by the indirect response model and integrated model, which will be helpful in understanding the detailed processes of erlotinib activity and determining an appropriate dosing regimen in clinical studies.

Modelling c-Abl Signalling in Activated Neutrophils: the Anti-inflammatory Effect of Seliciclib

When mammalian tissues are infected by bacteria or fungi, inflammatory cytokines are released that cause circulating neutrophils to invade the infected tissue. The cytosolic tyrosine kinase, c-Abl, in these tissue neutrophils is activated by TNFα. c-Abl then phosphorylates STAT transcription factors, which results in production of the antiapoptotic protein Mcl-1. The normally short-lived tissue neutrophils are then unable to enter apoptosis. c-Abl also causes release of reactive oxygen species (ROS) from the mitochondria of the activated neutrophils. These ROS, and ROS generated by NADPH oxidase, are bactericidal agents of the innate immune system. In some inflammatory diseases, such as chronic obstructive pulmonary disease (COPD), the invading neutrophils become permanently activated, and the resulting ROS overproduction causes severe tissue damage. The cyclin-dependent kinase inhibitor, seliciclib, blocks transcription through inhibition of cdk9. This results in a relatively rapid decline of antiapoptotic Mcl-1 transcripts in activated neutrophils, an increase in neutrophil apoptosis, and less ROS leakage and oxidative damage. We present here a model of neutrophil kinetics that simulates the principal pathways of c-Abl signalling and use it to explore possible treatment options for inflammatory lung disease.

An integrin-targeted, pan-isoform, phosphoinositide-3 kinase inhibitor, SF1126, has activity against multiple myeloma in vivo

PURPOSE

Multiple reports point to an important role for the phosphoinositide-3 kinase (PI3K) and AKT signaling pathways in tumor survival and chemoresistance in multiple myeloma (MM). The goals of our study were: (1) to generate the preclinical results necessary to justify a Phase I clinical trial of SF1126 in hematopoietic malignancies including MM and (2) to begin combining pan-PI3K inhibitors with other agents to augment antitumor activity of this class of agent in preparation for combination therapy in Phase I/II trials.

METHODS

We determined the in vitro activity of SF1126 with 16 human MM cell lines. In vivo tumor growth suppression was determined with human myeloma (MM.1R) xenografts in athymic mice. In addition, we provide evidence that SF1126 has pharmacodynamic activity in the treatment of patients with MM.

RESULTS

SF1126 was cytotoxic to all tested MM lines, and potency was augmented by the addition of bortezomib. SF1126 affected MM.1R cell line signaling in vitro, inhibiting phospho-AKT, phospho-ERK, and the hypoxic stabilization of HIF1α. Tumor growth was 94 % inhibited, with a marked decrease in both cellular proliferation (PCNA immunostaining) and angiogenesis (tumor microvessel density via CD31 immunostaining). Our clinical results demonstrate pharmacodynamic knockdown of p-AKT in primary patient-derived MM tumor cells in vivo.

CONCLUSIONS

Our results establish three important points: (1) SF1126, a pan-PI3K inhibitor has potent antitumor activity against MM in vitro and in vivo, (2) SF1126 displays augmented antimyeloma activity when combined with proteasome inhibitor, bortezomib/Velcade(®), and (3) SF1126 blocks the IGF-1-induced activation of AKT in primary MM tumor cells isolated from SF1126-treated patients The results support the ongoing early Phase I clinical trial in MM and suggest a future Phase I trial in combination with bortezomib in hematopoietic malignancies.